Modeling techniques such as machine learning are useful in many applications, such as email spam filtering, predicting fraudulent credit card charges, or analyzing customer churn, such as in a wireless carrier network, for example. For instance, in the case of credit card charges, data such as the amount of the charge, the geographic location, and the store identifier can be used by a model to predict whether the charge is fraudulent. In some cases, ensemble learning can be used where the predictions of multiple models are combined.